SOTAVerified

Word Sense Disambiguation

The task of Word Sense Disambiguation (WSD) consists of associating words in context with their most suitable entry in a pre-defined sense inventory. The de-facto sense inventory for English in WSD is WordNet.. For example, given the word “mouse” and the following sentence:

“A mouse consists of an object held in one's hand, with one or more buttons.”

we would assign “mouse” with its electronic device sense (the 4th sense in the WordNet sense inventory).

Papers

Showing 401450 of 1035 papers

TitleStatusHype
A Joint Sequential and Relational Model for Frame-Semantic Parsing0
Train-O-Matic: Large-Scale Supervised Word Sense Disambiguation in Multiple Languages without Manual Training Data0
SupWSD: A Flexible Toolkit for Supervised Word Sense DisambiguationCode0
Neural Sequence Learning Models for Word Sense Disambiguation0
Dict2vec : Learning Word Embeddings using Lexical DictionariesCode0
AutoExtend: Combining Word Embeddings with Semantic Resources0
Handling Homographs in Neural Machine Translation0
Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation0
Sense Contextualization in a Dependency-Based Compositional Distributional Model0
UWAV at SemEval-2017 Task 7: Automated feature-based system for locating puns0
The (too Many) Problems of Analogical Reasoning with Word Vectors0
N-Hance at SemEval-2017 Task 7: A Computational Approach using Word Association for Puns0
JU CSE NLP @ SemEval 2017 Task 7: Employing Rules to Detect and Interpret English Puns0
BuzzSaw at SemEval-2017 Task 7: Global vs. Local Context for Interpreting and Locating Homographic English Puns with Sense Embeddings0
NRU-HSE at SemEval-2017 Task 4: Tweet Quantification Using Deep Learning Architecture0
LIM-LIG at SemEval-2017 Task1: Enhancing the Semantic Similarity for Arabic Sentences with Vectors Weighting0
ELiRF-UPV at SemEval-2017 Task 7: Pun Detection and Interpretation0
ECNU at SemEval-2017 Task 7: Using Supervised and Unsupervised Methods to Detect and Locate English Puns0
SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity0
RUFINO at SemEval-2017 Task 2: Cross-lingual lexical similarity by extending PMI and word embeddings systems with a Swadesh's-like list0
SemEval-2017 Task 7: Detection and Interpretation of English Puns0
Semantic Frame Labeling with Target-based Neural Model0
ShotgunWSD: An unsupervised algorithm for global word sense disambiguation inspired by DNA sequencing0
Improve Lexicon-based Word Embeddings By Word Sense Disambiguation0
Unsupervised, Knowledge-Free, and Interpretable Word Sense DisambiguationCode0
Benben: A Chinese Intelligent Conversational Robot0
EuroSense: Automatic Harvesting of Multilingual Sense Annotations from Parallel Text0
English Event Detection With Translated Language Features0
Improved Word Representation Learning with SememesCode0
Bridge Text and Knowledge by Learning Multi-Prototype Entity Mention Embedding0
Uniformisation de corpus anglais annot\'es en sens (Unification of sense annotated English corpora for word sense disambiguation)0
Repr\'esentation vectorielle de sens pour la d\'esambigu\" lexicale \`a base de connaissances (Sense Embeddings in Knowledge-Based Word Sense Disambiguation)0
Book Review: Linked Lexical Knowledge Bases Foundations and Applications by Iryna Gurevych, Judith Eckle-er and Michael Matuschek0
Using Pseudowords for Algorithm Comparison: An Evaluation Framework for Graph-based Word Sense Induction0
Duluth at Semeval-2017 Task 7 : Puns upon a midnight dreary, Lexical Semantics for the weak and weary0
Comparison of Global Algorithms in Word Sense Disambiguation0
Creating and Validating Multilingual Semantic Representations for Six Languages: Expert versus Non-Expert Crowds0
Arabic Diacritization: Stats, Rules, and Hacks0
A Preliminary Study of Croatian Lexical Substitution0
A Layered Language Model based Hybrid Approach to Automatic Full Diacritization of Arabic0
Supervised and unsupervised approaches to measuring usage similarity0
Word Sense Filtering Improves Embedding-Based Lexical Substitution0
Word Similarity Datasets for Indian Languages: Annotation and Baseline Systems0
Supervised and Unsupervised Word Sense Disambiguation on Word Embedding Vectors of Unambigous Synonyms0
Using Linked Disambiguated Distributional Networks for Word Sense Disambiguation0
Addressing Problems across Linguistic Levels in SMT: Combining Approaches to Model Morphology, Syntax and Lexical Choice0
Applying Multi-Sense Embeddings for German Verbs to Determine Semantic Relatedness and to Detect Non-Literal Language0
Multilingual CALL Framework for Automatic Language Exercise Generation from Free Text0
Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison0
BabelDomains: Large-Scale Domain Labeling of Lexical Resources0
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1COSINE + Transductive LearningAccuracy85.3Unverified
2PaLM 540B (finetuned)Accuracy78.8Unverified
3ST-MoE-32B 269B (fine-tuned)Accuracy77.7Unverified
4DeBERTa-EnsembleAccuracy77.5Unverified
5Vega v2 6B (fine-tuned)Accuracy77.4Unverified
6UL2 20B (fine-tuned)Accuracy77.3Unverified
7Turing NLR v5 XXL 5.4B (fine-tuned)Accuracy77.1Unverified
8T5-XXL 11BAccuracy76.9Unverified
9DeBERTa-1.5BAccuracy76.4Unverified
10ST-MoE-L 4.1B (fine-tuned)Accuracy74Unverified
#ModelMetricClaimedVerifiedStatus
1SANDWiCHSenseval 287.8Unverified
2GlossGPTSenseval 286.1Unverified
3ConSeC+WNGCSenseval 282.7Unverified
4ESR+WNGCSenseval 282.5Unverified
5ConSeCSenseval 282.3Unverified
6ESCHER SemCorSenseval 281.7Unverified
7ESRSenseval 281.3Unverified
8EWISER+WNGCSenseval 280.8Unverified
9SemCor+WNGC, hypernymsSenseval 279.7Unverified
10SparseLMMS+WNGCSenseval 279.6Unverified
#ModelMetricClaimedVerifiedStatus
1Human BenchmarkAccuracy0.81Unverified
2ruT5-large-finetuneAccuracy0.74Unverified
3RuBERT conversationalAccuracy0.73Unverified
4RuBERT plainAccuracy0.73Unverified
5ruRoberta-large finetuneAccuracy0.72Unverified
6ruBert-base finetuneAccuracy0.71Unverified
7Multilingual BertAccuracy0.69Unverified
8ruT5-base-finetuneAccuracy0.68Unverified
9ruBert-large finetuneAccuracy0.68Unverified
10SBERT_Large_mt_ru_finetuningAccuracy0.66Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF178.7Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF172.63Unverified
3LSTMLP (T:SemCor, U:1K)F169.5Unverified
4LSTMLP (T:OMSTI, U:1K)F168.1Unverified
5LSTMLP (T:SemCor, U:OMSTI)F167.9Unverified
6LSTM (T:OMSTI)F167.3Unverified
7GASext (Concatenation)F167.2Unverified
8GASext (Linear)F167.1Unverified
9GAS (Concatenation)F167Unverified
10LSTM (T:SemCor)F167Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF179.7Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF175.15Unverified
3LSTMLP (T:OMSTI, U:1K)F174.4Unverified
4LSTMLP (T:SemCor, U:OMSTI)F173.9Unverified
5LSTMLP (T:SemCor, U:1K)F173.8Unverified
6LSTM (T:SemCor)F173.6Unverified
7GASext (Linear)F172.4Unverified
8LSTM (T:OMSTI)F172.4Unverified
9GASext (Concatenation)F172.2Unverified
10GAS (Concatenation)F172.1Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF177.8Unverified
2LSTMLP (T:SemCor, U:1K)F171.8Unverified
3LSTMLP (T:SemCor, U:OMSTI)F171.1Unverified
4LSTMLP (T:OMSTI, U:1K)F171Unverified
5GASext (Concatenation)F170.5Unverified
6GAS (Concatenation)F170.2Unverified
7SemCor+WNGT, vocabulary reduced, ensembleF170.11Unverified
8GASext (Linear)F170.1Unverified
9GAS (Linear)F170Unverified
10LSTM (T:SemCor)F169.2Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF190.4Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF186.02Unverified
3kNN-BERT + POS (training corpus: WNGT)F185.32Unverified
4LSTMLP (T:SemCor, U:OMSTI)F184.3Unverified
5LSTMLP (T:SemCor, U:1K)F183.6Unverified
6LSTMLP (T:OMSTI, U:1K)F183.3Unverified
7LSTM (T:SemCor)F182.8Unverified
8ShotgunWSD 2.0F181.22Unverified
9kNN-BERTF181.2Unverified
10LSTM (T:OMSTI)F181.1Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF173.4Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF166.81Unverified
3LSTM (T:SemCor)F164.2Unverified
4LSTMLP (T:SemCor, U:OMSTI)F163.7Unverified
5LSTMLP (T:SemCor, U:1K)F163.5Unverified
6LSTMLP (T:OMSTI, U:1K)F163.3Unverified
7kNN-BERT + POS (training corpus: SemCor)F163.17Unverified
8kNN-BERTF160.94Unverified
9LSTM (T:OMSTI)F160.7Unverified
#ModelMetricClaimedVerifiedStatus
1GlossGPTF1 (Zeroshot Dev)81.8Unverified
2ESR LargeF1 (Zeroshot Dev)77.4Unverified
3ESR baseF1 (Zeroshot Dev)73.9Unverified
4SEMEq LargeF1 (Zeroshot Dev)73.7Unverified
5SEMeq baseF1 (Zeroshot Dev)71.5Unverified
6RTWE largeF1 (Zero shot test)69.9Unverified
7LeskF1 (Zeroshot Dev)40.1Unverified
8MFSF1 (Zeroshot Dev)0Unverified
#ModelMetricClaimedVerifiedStatus
1HumanTask 3 Accuracy: all85.3Unverified
2transformersTask 1 Accuracy: all77.8Unverified
3CTLRTask 1 Accuracy: all76.8Unverified
4GlossBert-wsTask 1 Accuracy: all75.9Unverified
5Bert-baseTask 1 Accuracy: all75.3Unverified
6Unsupervised BertTask 1 Accuracy: all54.4Unverified
7FastTextTask 1 Accuracy: all53.7Unverified
8All trueTask 1 Accuracy: all50.8Unverified
#ModelMetricClaimedVerifiedStatus
1Chinchilla-70B (few-shot, k=5)Accuracy69.1Unverified
2Gopher-280B (few-shot, k=5)Accuracy56.4Unverified
3OPT 175BAccuracy49.1Unverified
4GAL 120B (few-shot, k=5)Accuracy48.7Unverified
5GAL 30B (few-shot, k=5)Accuracy47Unverified
6BLOOM 176BAccuracy1.3Unverified
#ModelMetricClaimedVerifiedStatus
1UKBppr_w2wSenseval 268.8Unverified
2KEFAll68Unverified
3WSD-TMAll66.9Unverified
4BabelfyAll65.5Unverified
5WN 1st sense baselineAll65.2Unverified
6UKBppr_w2w-nfAll57.5Unverified
#ModelMetricClaimedVerifiedStatus
1SemCor+WNGC, hypernymsF182.6Unverified
2SemCor+WNGT, vocabulary reduced, ensembleF174.46Unverified
3GASext (Concatenation)F172.6Unverified
4GASext (Linear)F172.1Unverified
5GAS (Concatenation)F171.8Unverified
6GAS (Linear)F171.6Unverified
#ModelMetricClaimedVerifiedStatus
1kNN-BERTF180.12Unverified
2IMS + adapted CWF173.4Unverified
3BiLSTM with GloVeF173.4Unverified
4Single BiLSTMF172.5Unverified
#ModelMetricClaimedVerifiedStatus
1kNN-BERTF176.52Unverified
2BiLSTM with GloVeF166.9Unverified
3IMS + adapted CWF166.2Unverified
#ModelMetricClaimedVerifiedStatus
1SPINSequence Recovery %(All)30.3Unverified